Near-Sensor Reservoir Computing for Gait Recognition via a Multi-Gate Electrolyte-Gated Transistor.
Near-Sensor Reservoir Computing for Gait Recognition via a Multi-Gate Electrolyte-Gated Transistor.
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DOI：
10.1002/advs.202300471
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发表时间：
2023-05
期刊：
影响因子：
15.1
通讯作者：
Li, Run-Wei
中科院分区：
文献类型：
--
作者：
Liu, Xuerong;Sun, Cui;Guo, Zhecheng;Xia, Xiangling;Jiang, Qian;Ye, Xiaoyu;Shang, Jie;Zhang, Yuejun;Zhu, Xiaojian;Li, Run-Wei
关键词：
近年来，各种智能可穿戴电子产品的出现，促进了人机交互、医疗健康监测等技术的快速发展。不幸的是，使用传统的非现场数字计算机处理多个可穿戴传感器获取的冗余运动和生理数据通常会导致严重的延迟和能耗问题。在这项工作中，报道了一种基于多栅极电解质门控晶体管（EGT）的高效多通道近传感器计算存储装置。EGT在电压调制下表现出丰富的短期动态特性，可以实现时间序列信号的非线性并行积分，从而提取输入中的同步状态和集体频率等时间特征。与压力传感器集成的柔性EGT可以进行现场步态信息分析，从而识别运动行为和帕金森病。这种近传感器储层计算系统为快速分析运动和生理信号提供了新的途径，大大提高了效率，并将导致强大的智能柔性可穿戴电子产品。本研究报告了一种基于多通道电解质门控过渡（EGT）的储层装置，该装置能够并行集成和处理多通道流信号。该储层可以与多个压力传感器集成，以提取时间特征，包括感官输入中的同步状态和集体频率。实现了双足运动时步态模式的准确识别，为智能可穿戴电子产品提供了新的思路。
The recent emergence of various smart wearable electronics has furnished the rapid development of human–computer interaction, medical health monitoring technologies, etc. Unfortunately, processing redundant motion and physiological data acquired by multiple wearable sensors using conventional off‐site digital computers typically result in serious latency and energy consumption problems. In this work, a multi‐gate electrolyte‐gated transistor (EGT)‐based reservoir device for efficient multi‐channel near‐sensor computing is reported. The EGT, exhibiting rich short‐term dynamics under voltage modulation, can implement nonlinear parallel integration of the time‐series signals thus extracting the temporal features such as the synchronization state and collective frequency in the inputs. The flexible EGT integrated with pressure sensors can perform on‐site gait information analysis, enabling the identification of motion behaviors and Parkinson's disease. This near‐sensor reservoir computing system offers a new route for rapid analysis of the motion and physiological signals with significantly improved efficiency and will lead to robust smart flexible wearable electronics. This work reports a multi‐gate electrolyte‐gated transitior (EGT)‐based reservoir device capable of parallel integrating and processing multi‐channel streaming signals. This reservoir can be integrated with multiple pressure sensors to extract the temporal features including the synchronization state and collective frequency in the sensory inputs. Accurate identification of gait patterns during bipedal movement is realized, providing new ideas for smart wearable electronics.
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